The present invention relates to a fingerprint ID system and method which permits real-time comparison of fingerprint image data with previously stored image data.
Fingerprints are utilized as most reliable means to identify individuals because of two outstanding characteristics that they remain unchanged all through life and differ from individual to individual. The features that are used for fingerprint identification are a break point (or end point) of a bulge line (a convexity of a fingerprint pattern) and a point where the bulge line branches (a branch point); these features are generically called minutiae. Since the matching of a fingerprint as an image is encountered with difficulties in the file capacity and matching speed, the fingerprint identification is carried out using the positional relationship of features or minutiae that are extracted from the fingerprint image. The extraction of minutiae from the input fingerprint image begins with the correction of the original image by smoothing and emphasizing, followed by detecting the orientation of the fingerprint pattern. A binary bulge line image is formed by local two-dimensional differential filtering and threshold processing on the basis of the detected orientation. The bulge line image is subjected to thinning processing to detect the positions of minutiae and the direction of the bulge line is measured for each minutia. Furthermore, the number of intersecting bulge lines is detected as the relationship between neighboring minutiae, by which the position coordinate of each minutia, the pattern orientation and the relationship between neighboring minutiae are listed. The input fingerprint is compared with the previously registered fingerprint by checking individual minutiae of the former against those of the latter.
There has been proposed a fingerprint ID system of the type that compares in real time the input fingerprint image data with registered data to identify individuals. This fingerprint ID system uses a general-purpose microprocessor to perform pre-processing for removing noise from the input image, binary processing for converting the pixel value of image data to a binary value "1" or "0" through use of a predetermined threshold value, thinning processing for extracting a figure of the same line width from the binary image, processing for extracting minutiae and pattern matching. In other words, the microprocessor performs the whole image processing.
In the conventional fingerprint ID system, however, image processing for fingerprint identification is carried out exclusively by the general-purpose microprocessor; hence, the processing time increases in proportion to the amount of data to be processed and the complexity of processing, slowing down the system's response in the fingerprint identification.
That is, in image processing by computer software, for example, when 512- by 512-pixel image data is processed for thinning by sequentially scanning it in 3- by 3-pixel blocks, the image data is scanned 510 by 510 times. In the thinning process for extracting a figure of binary image data as a line figure of the same line width without impairing its continuity, it is necessary that: the line width be kept constant; the line be positioned at the center of the original figure; the continuity of the figure be maintained; and end points of the figure not be reduced. In addition, processing is needed to suppress the generation of whiskers in concave and convex portion of the fingerprint between bulge lines and at their intersections. Thus, an appreciably large number of processing steps are involved in the entire image processing.
The above-mentioned scanning for thinning is repeated until it converges all over the display image. Hence, the reduction of the response time of the fingerprint ID system calls for improving the thinning scheme and the hardware configuration therefor.
By mounting hardware exclusive for image processing, the response time could be shortened, but it is undesirable to incorporate such hardware in the fingerprint ID system which is a consumer product required to be low-cost and small-sized and the mounting hardware exclusive for image processing is inferior to software processing by a computer in terms of systems extensibility.
Besides, the prior art fingerprint ID system utilizes either one of minutia matching and template matching schemes. The minutia matching scheme is excellent in that it ensures stable matching even if the fingerprint to be examined becomes misaligned by rotational movement, but all fingerprints do not have clear minutiae and bulge lines may Sometimes be totally flat or unclear. In such a situation, the template matching scheme may provide a higher rate in recognition. That is, the fingerprint ID system of the type using the minutia matching scheme alone cannot always acheive a high success rate in recognition.